Type Artificial Intelligence Software


The analysis of the timeline helps to identify the required approach and handling of single vulnerabilities and vulnerability collections. This overview makes it possible to see less important slices and more severe hotspots at a glance. Initiating immediate vulnerability response and prioritizing of issues is possible.

Vendor »

Identifying all affected vendors is a good starting point for an overview. This makes it possible to determine an homogeneous landscape or the most important hotspots in heterogeneous landscapes.

Product »

Grouping vulnerabilities by products helps to get an overview. This makes it possible to determine an homogeneous landscape or the most important hotspots in heterogeneous landscapes.

Remediation »

Vendors and researchers are eager to find countermeasures to mitigate security vulnerabilities. These can be distinguished between multiple forms and levels of remediation which influence risks differently.

Exploitability »

Researcher and attacker which are looking for security vulnerabilities try to exploit them for academic purposes or personal gain. The level and quality of exploitability can be distinguished to determine simplicity and strength of attacks.

Access Vector »

The approach a vulnerability it becomes important to use the expected access vector. This is typically via the network, local, or physically even.

Authentication »

To exploit a vulnerability a certail level of authentication might be required. Vulnerabilities without such a requirement are much more popular.

User Interaction »

Some attack scenarios require some user interaction by a victim. This is typical for phishing, social engineering and cross site scripting attacks.

C3BM Index »

Our unique C3BM Index (CVSSv3 Base Meta Index) cumulates the CVSSv3 Meta Base Scores of all entries over time. Comparing this index to the amount of disclosed vulnerabilities helps to pinpoint the most important events.

CVSSv3 Base »

The Common Vulnerability Scoring System (CVSS) is an industry standard to define the characteristics and impacts of security vulnerabilities. The base score represents the intrinsic aspects that are constant over time and across user environments. Our unique meta score merges all available scores from different sources to aggregate to the most reliable result.

CVSSv3 Temp »

The Common Vulnerability Scoring System (CVSS) uses temp scores to reflect the characteristics of a vulnerability that may change over time but not across user environments. This includes reporting confidence, exploitability and remediation levels. We do also provide our unique meta score for temp scores, even though other sources rarely publish them.

VulDB »

The moderation team is always defining the base vector and base score for an entry. These and all other available scores are used to generate the meta score.


The National Vulnerability Database (NVD) is also defining CVSS vectors and scores. These are usually not complete and might differ from VulDB scores.

Vendor »

Some vendors are willing to publish their own CVSS vectors and scores for vulnerabilities in their products. The coverage varies from vendor to vendor.

Research »

There are sometimes also security researcher which provide their own CVSS vectors and scores for vulnerabilities they have found and published.

Exploit 0-day »

The moderation team is working with the threat intelligence team to determine prices for exploits. Our unique algorithm is used to identify the 0-day prices for an exploit, before it got distributed or became public. Calculated prices are aligned to prices disclosed by vulnerability broker and compared to prices we see on exploit markets.

Exploit Today »

The 0-day prices do not consider time-relevant factors. The today price does reflect price impacts like disclosure of vulnerability details, alternative exploits, availability of countermeasures. These dynamic aspects might decrease the exploit prices over time. Under certain circumstances this happens very fast.

Exploit Market Volume »

Our unique calculation of exploit prices makes it possible to forecast the expected exploit market volume. The calculated prices for all possible 0-day expoits are cumulated for this task. Comparing the volume to the amount of disclosed vulnerabilities helps to pinpoint the most important events.

🔴 CTI Activities »

Our unique Cyber Threat Intelligence aims to determine the ongoing research of actors to anticipiate their acitivities. Observing exploit markets on the Darknet, discussions of vulnerabilities on mailinglists, and exchanges on social media makes it possible to identify planned attacks. Monitored actors and activities are classified whether they are offensive or defensive. They are also weighted as some actors are well-known for certain products and technologies. And some of their disclosures might contain more or less details about technical aspects and personal context. The world map highlights active actors in real-time.

Affected Products (20): Amazon Echo, Amazon Echo Dot, Amazon Echo Show, Amazon Echo Spot, Artificial Intelligence Theme, Google TensorFlow, Mycroft AI, Petalk Petalk AI, Petalk PF-103, Petwant Petalk AI, Petwant PF-103, Sofy.AI Plugin, SUSI.AI, TensorFlow, toucbase.ai, touchbase.ai, Webexceluk P.A.I.D, Xiaomi AI Speaker, Xiaomi AI speaker MDZ-25-DT, Yeelight Smart AI Speaker

07/25/20212.02.0Amazon Echo Dot Factory Reset information disclosureEcho DotNot DefinedWorkaround1.58+CVE-2021-37436
06/30/20214.64.5Google TensorFlow Archive tf.keras.utils.get_file unknown vulnerabilityTensorFlowNot DefinedNot Defined0.07CVE-2021-35958
05/15/20214.94.7Google TensorFlow tf.transpose exceptional conditionTensorFlowNot DefinedOfficial Fix0.06CVE-2021-29618
05/15/20214.94.7Google TensorFlow tf.strings.substr exceptional conditionTensorFlowNot DefinedOfficial Fix0.00CVE-2021-29617
05/15/20214.34.1Google TensorFlow attr_value_util.cc ParseAttrValue recursionTensorFlowNot DefinedOfficial Fix0.05CVE-2021-29615
05/15/20216.36.0Google TensorFlow tf.raw_ops.CTCLoss initializationTensorFlowNot DefinedOfficial Fix0.07CVE-2021-29613
05/15/20216.36.0Google TensorFlow common.c TFLiteIntArray integer overflowTensorFlowNot DefinedOfficial Fix0.00CVE-2021-29605
05/15/20214.34.1Google TensorFlow tf.raw_ops.IRFFT assertionTensorFlowNot DefinedOfficial Fix0.00CVE-2021-29562
05/15/20214.34.1Google TensorFlow FPE Runtime tf.raw_ops.SparseMatMul divide by zeroTensorFlowNot DefinedOfficial Fix0.05CVE-2021-29557
05/15/20214.34.1Google TensorFlow tf.raw_ops.SparseCountSparseOutput exceptional conditionTensorFlowNot DefinedOfficial Fix0.06CVE-2021-29619
05/15/20216.36.0Google TensorFlow banded_triangular_solve_op.cc tf.raw_ops.BandedTriangularSolve buffer overflowTensorFlowNot DefinedOfficial Fix0.05CVE-2021-29612
05/15/20216.36.0Google TensorFlow sparse_reshape_op.cc SparseReshape initializationTensorFlowNot DefinedOfficial Fix0.00CVE-2021-29611
05/15/20217.06.7Google TensorFlow quantize_and_dequantize_op.cc tf.raw_ops.QuantizeAndDequantizeV2 initializationTensorFlowNot DefinedOfficial Fix0.00CVE-2021-29610
05/15/20216.36.0Google TensorFlow sparse_add_op.cc initializationTensorFlowNot DefinedOfficial Fix0.00CVE-2021-29609
05/15/20217.06.7Google TensorFlow ragged_tensor_to_tensor_op.cc tf.raw_ops.RaggedTensorToTensor heap-based overflowTensorFlowNot DefinedOfficial Fix0.05CVE-2021-29608
05/15/20216.36.0Google TensorFlow sparse_sparse_binary_op_shared.cc SparseAdd unusual conditionTensorFlowNot DefinedOfficial Fix0.00CVE-2021-29607
05/15/20216.36.0Google TensorFlow TFLite Model split_v.cc Split_V out-of-bounds readTensorFlowNot DefinedOfficial Fix0.00CVE-2021-29606
05/15/20214.34.1Google TensorFlow hashtable_lookup.cc divide by zeroTensorFlowNot DefinedOfficial Fix0.05CVE-2021-29604
05/15/20216.36.0Google TensorFlow TFLite Model arg_min_max.cc ArgMax out-of-bounds writeTensorFlowNot DefinedOfficial Fix0.05CVE-2021-29603
05/15/20216.36.0Google TensorFlow concatenation.cc integer overflowTensorFlowNot DefinedOfficial Fix0.06CVE-2021-29601
05/15/20214.34.1Google TensorFlow conv.cc divide by zeroTensorFlowNot DefinedOfficial Fix0.05CVE-2021-29594
05/15/20216.36.0Google TensorFlow subgraph.c null pointer dereferenceTensorFlowNot DefinedOfficial Fix0.00CVE-2021-29592
05/15/20214.34.1Google TensorFlow while.cc While infinite loopTensorFlowNot DefinedOfficial Fix0.06CVE-2021-29591
05/15/20214.34.1Google TensorFlow pooling.cc divide by zeroTensorFlowNot DefinedOfficial Fix0.04CVE-2021-29586
05/15/20214.34.1Google TensorFlow TFLite padding.h divide by zeroTensorFlowNot DefinedOfficial Fix0.06CVE-2021-29585

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